Three-dimensional scanning and digitization of the surface geometry of objects is commonly used in many industries and services, and their applications are numerous. The shape of an object is scanned and digitized using a ranging sensor that measures the distance between the sensor and a set of points on the surface. The sensor captures a section of the object's surface from a given viewpoint. To extend the scanned section or to scan the whole surface, the sensor, or the object, is moved to one of several viewpoints and the spatial relationship between all the relative poses between the sensor and the object is obtained.
Several approaches exist for measuring and calculating these spatial relationships. One of these approaches exploits the shape of the observed object to calculate the relative sensor position and orientation, namely its pose, in space. These shape-based approaches reduce the time to set up the acquisition since there is no need to affix targets or additional references in the scene. An observed shape section may still be insufficiently complex in its shape to ensure that the pose be reliably estimated. There are well known situations such as a planar, spherical, cylindrical surface, and others where it is not possible to unambiguously determine the six degrees of freedom of the sensor pose. In the presence of noise, even non ideal cases may lead to unreliable pose estimation.